Nuclear medicine is a unique medical specialty wherein radiation is used to acquire images which show the function and anatomy of organs, bones or tissues of the body. Radiopharmaceuticals are introduced into the body, either by injection or ingestion, and are attracted to specific organs, bones or tissues of interest. Such radiopharmaceuticals produce gamma photon emissions which emanate from the body and are captured by a scintillation crystal, with which the photons interact to produce flashes of light or “events.” Events are detected by an array of photodetectors, such as photomultiplier tubes, and their spatial locations or positions are calculated and stored. In this way, an image of the organ or tissue under study is created from detection of the distribution of the radioisotopes in the body.
One particular nuclear medicine imaging technique is known as Positron Emission Tomography, or PET. PET is used to produce images for diagnosing the biochemistry or physiology of a specific organ, tumor or other metabolically active site. Measurement of the tissue concentration of a positron emitting radionuclide is based on coincidence detection of the two gamma photons arising from positron annihilation. When a positron is annihilated by an electron, two 511 keV gamma photons are simultaneously produced and travel in approximately opposite directions. Gamma photons produced by an annihilation event can be detected by a pair of oppositely disposed radiation detectors capable of producing a signal in response to the interaction of the gamma photons with a scintillation crystal. Annihilation events are typically identified by a time coincidence between the detection of the two 511 keV gamma photons in the two oppositely disposed detectors, i.e., the gamma photon emissions are detected virtually simultaneously by each detector. When two oppositely disposed gamma photons each strike an oppositely disposed detector to produce a time coincidence event, they also identify a line of response, or LOR, along which the annihilation event has occurred. An example of a PET method and apparatus is described in U.S. Pat. No. 6,858,847, which patent is incorporated herein by reference in its entirety.
After being sorted into parallel projections, the LORs defined by the coincidence events are used to reconstruct a three-dimensional distribution of the positron-emitting radionuclide within the patient. In two-dimensional PET, each 2D transverse section or “slice” of the radionuclide distribution is reconstructed independently of adjacent sections. In fully three-dimensional PET, the data are sorted into sets of LORs, where each set is parallel to a particular detector angle, and therefore represents a two dimensional parallel projection p(s, φ) of the three dimensional radionuclide distribution within the patient, where s corresponds to the distance of the imaging plane perpendicular to the scanner axis and φ corresponds to the angle of the detector plane with respect to the x axis in (x, y) coordinate space (in other words, φ corresponds to a particular LOR direction). Coincidence events are integrated or collected for each LOR and stored as a sinogram. In this format, a single fixed point in f (x,y) traces a sinusoid in the sinogram. In each sinogram, there is one row containing the LORs for a particular azimuthal angle φ; each such row corresponds to a one-dimensional parallel projection of the tracer distribution at a different coordinate along the scanner axis. This is shown conceptually in FIG. 1.
An event is registered if both crystals detect an annihilation photon within a coincidence time window τ (e.g., on the order of 4-5 ns), depending on the timing properties of the scintillator and the field of view. A pair of detectors is sensitive only to coincidence events occurring in the volume between the two detectors, thereby eliminating the need for physical collimation, and thus significantly increasing sensitivity. Accurate corrections can be made for the self-absorption of photons within the patient (i.e., attenuation correction) so that accurate measurements of tracer concentration can be made.
The number of time coincidences detected per second within a field of view (FOV) of a detector is the count rate of the detector. The count rate at each of two oppositely disposed detectors, A and B, can be referred to as singles counts, or singles, SA and SB. The time required for a gamma photon to travel from its point of origin to a point of detection is referred to as the time of flight, or TOF, of the gamma photon. TOF is dependent upon the speed of light c and the distance traveled. A time coincidence, or coincidence event, is identified if the time difference between the arrival of signals in a pair of oppositely disposed detectors is within the coincidence time window τ. In conventional PET, the coincidence detection time window τ is wide enough so that an annihilation event occurring anywhere within the object would produce annihilation gamma photons reaching their respective detectors within the coincidence window. Coincidence time windows of 4.5-12 nsec are common for conventional PET, and are largely determined by the time resolution capabilities of the detectors and electronics.
As illustrated in FIG. 2, if an annihilation event occurs at the midpoint of a LOR, the TOF of the gamma photon detected in detector A (TA) is equal to the TOF of the gamma photon detected in detector B (TB). If an annihilation event occurs at a distance Δx from the midpoint of the LOR, the difference between TA and TB is Δt=2Δx/c, where c is the speed of light. If d is the distance between the detectors, the TOF difference Δt could take any value from −d/c to +d/c, depending on the location of the annihilation event.
In contrast to conventional PET, time-of-flight positron emission tomography (“TOF-PET”) is based on the measurement of the difference Δt between the detection times of the two gamma photons arising from the positron annihilation event. This measurement allows the annihilation event to be localized along the LOR with a resolution of about 75-180 mm FWHM, assuming a time resolution of 500-1200 ps (picoseconds). Though less accurate than the spatial resolution of the scanner, this approximate localization is effective in reducing noise contributions both from random coincidence events and from true coincidences that actually originated elsewhere in the object. This improves both the stability of the reconstruction and the signal-to-noise ratio (SNR) in the final image, especially when imaging large objects. TOF-PET may increase image SNR by a factor of 2 or more compared to conventional PET.
TOF scanners developed in the early 1980s were used for research and clinical applications, but the SNR gain provided by the TOF measurements of about 500 ps resolution was offset by poorer spatial resolution and lower sensitivity due to the low stopping power of the BaF2 and CsF scintillation crystals used in such scanners. Consequently, those TOF systems could not compete successfully with conventional (non-TOF) BGO scanners. As a result, TOF-PET almost completely disappeared from the scene in the 1990s. Today, faster electronics and crystals such as LSO and LaBr3 reopen the prospect of exploiting the TOF information without compromising other parameters such as the count rate, the sensitivity, and the energy and spatial resolutions.
Septumless or “3D” PET scanners (i.e., without interplane septa) currently constitute a large percentage of the total market for PET imaging. Because of the lack of interplane septa, scattered events (i.e., annihilation photons undergoing Compton scattering before reaching the detector) may represent a large portion of the measured data (e.g., up to 50% or more in clinical studies). An example of such scatter is shown in FIG. 3, which illustrates a septumless PET scanner utilizing a ring detector configuration, which is also applicable for use with the present invention.
An annihilation event occurring at emission point 21 produces two oppositely traveling gamma photons along LOR 22. One of the gamma photons, however, may undergo Compton scattering at scatter point 23, which changes its travel direction to path 24. Consequently, while the first gamma photon is detected by detector A in line with the originating LOR 22, the scattered gamma photon will be detected in detector B, instead of by detector C. Consequently, the coincidence event detected in detectors A and C will result in a false LOR 25 being identified, instead of the correct LOR 22.
Accordingly, much effort has been devoted in the prior art to scatter correction techniques for conventional (i.e., non TOF) PET. With the broad coincidence time windows associated with conventional PET, the probability of detection of a scattered event does not depend significantly on the point of origin of the annihilation event along the LOR (see multiple points along LOR 22 in FIG. 3), and thus the scatter correction algorithm for conventional PET does not take into account the differential TOF of the scattered photon pair. The following articles are exemplary of the prior art development of the “single scatter simulation” (SSS) algorithm that is widely used in conventional PET:
1) J. S. Barney, J. G. Rogers, R. Harrop and H. Hoverath, “Object Shape Dependent Scatter Simulations,” IEEE Trans. Nuc. Sci., 38, 719-725, 1991.
2) J. M. Ollinger and G. C. Johns, “Model-Based Scatter Correction for Fully 3D PET,” 1993 IEEE Med. Img. Conf. Rec., 2, 1264-1268, 1994.
3) L. G. Hiltz and B. T. A. McKee, “Scatter correction for three-dimensional PET based on an analytic model dependent on source and attenuating object,” Phys. Med. Biol., 39, 2059-2071, 1994.
4) J. M. Ollinger, “Model-Based Scatter Correction for Fully 3D PET,” Phys. Med. Biol., 41, 153-176, 1996.
5) C. C. Watson, D. Newport and M. E. Casey, “A Single Scatter Simulation Technique for Scatter Correction in 3D PET,” in Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine, P. Grangeat and J.-L. Amans (eds.), Kluwer Academic Publishers, Dordrecht, 1996, pp. 255-268.
6) C. C. Watson, D. Newport, M. E. Casey, R. A. deKemp, R. S. Beanlands, and M. Schmand, “Evaluation of simulation-based scatter correction for 3-D PET cardiac imaging,” IEEE Trans. Nuc. Sci., vol. 44, pp. 90-97, February 1997.
7) C. C. Watson, “New, faster, image-based scatter correction for 3D PET,” IEEE Trans. Nucl. Sci., vol. 47, pp. 1587-94, 2000.
8) Werling A, Bublitz O, Doll J, Adam L E, Brix G, “Fast implementation of the single scatter simulation algorithm and its use in iterative image reconstruction of PET data,” Phys Med Biol., 47, 2947-60, 2002
9) Watson C C, Casey M E, Michel C, Bendriem B. “Advances in scatter correction for 3D PET/CT.” In: 2004 IEEE Nuclear Science Symposium Conference Record [book on CD-ROM]. Piscataway, N.J.: IEEE; 2004:M5-166.
10) Accorsi R, Adam L E, Werner M E, Karp J S, “Optimization of a fully 3D single scatter simulation algorithm for 3D PET,” Phys Med Biol., 49, 2577-98, 2004.
However, it is to be expected that scatter correction techniques developed for conventional PET may not be adequate for TOF PET, particularly those model-based algorithms that simulate scatter contributions. This is because the scattered and unscattered radiation follow distinct paths through the object, and therefore, for a given time offset, the portion of the emission distribution that may contribute to a detector pair is distinct for the scattered and unscattered radiation. Thus the scatter contribution to a given LOR may vary with time offset differently than the variation in true (unscattered) coincidences. An accurate scatter correction algorithm must correctly account for the time offsets of detected scattered photon pairs.
The following articles are the only prior art that the inventor is currently aware of that discuss scatter correction for TOF-PET. They propose algorithms that are quite different from the method provided by the present invention:
B Bendriem, F Soussaline, R Campagnolo, B Verrey, P Wajngerg, and A Syrota, “A Technique for the Correction of Scattered Radiation in a PET System Using Time-of-Flight Information,” J. Comput. Assist. Tomgr., 10, 287-295, 1986.
M Conti, B Bendriem, M Casey, M Chen, F Kehren, C Michel and V Panin, “Implementation of Time-Of-Flight on CPS HiRez PET scanner.” In: 2004 IEEE Nuclear Science Symposium Conference Record [book on CD-ROM]. Piscataway, N.J.: IEEE; 2004:M3-1.
M Conti, B Bendriem, M Casey, M Chen, F Kehren, C Michel and V Panin, “First experimental results of time-of-flight reconstruction on an LSO PET scanner.” Phys. Med Biol., vol. 50, pp. 4507-4526, 2005.